Cite Article
Cite Article
MLA
Alrashidi, Muhammad, et al. "Social Recommender System Based on CNN Incorporating Tagging and Contextual Features." JCIT vol.26, no.1 2024: pp.1-20. http://doi.org/10.4018/JCIT.335524
APA
Alrashidi, M., Selamat, A., Ibrahim, R., & Fujita, H. (2024). Social Recommender System Based on CNN Incorporating Tagging and Contextual Features. Journal of Cases on Information Technology (JCIT), 26 (1), 1-20. http://doi.org/10.4018/JCIT.335524
Chicago
Alrashidi, Muhammad, et al. "Social Recommender System Based on CNN Incorporating Tagging and Contextual Features," Journal of Cases on Information Technology (JCIT) 26, no.1: 1-20. http://doi.org/10.4018/JCIT.335524
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Journal of Cases on Information Technology (JCIT) The
Journal of Cases on Information Technology (JCIT) publishes comprehensive, real-life teaching cases, empirical and applied research-based case studies, and case studies based on individual, organizational, and societal experiences related to the utilization and management of information technology. Cases published in JCIT deal with a wide variety of organizations such as businesses, government organizations, educational institutions, libraries, non-profit organizations, and so forth. Additionally, cases published in JCIT report not only successful utilization of IT applications, but also failures and mismanagement of IT resources and applications. In addition to full-length cases and articles, JCIT periodically publishes teaching notes on innovative teaching approaches and critical incidents (short cases intended for use in a single class period). As a refereed, international journal, the JCIT provides effective understanding, solutions, and lessons learned in the utilization and management of information systems applications, technology, and resources. The impact of technology in a particular setting is described, analyzed, and synthesized for the objective of offering solutions for successful strategies.
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